[1A3] Project nautilUS +: a fully autonomous robotic technology for smart floor thickness monitoring of hazardous liquid storage tanks
A Rahbarimanesh¹ and M Burrows²
¹University of Manchester, UK
²RS Group plc, UK
Project nautilUS was a £1 million InnovateUK-funded project that managed to develop a small intrinsically safe and potentially ATEX-certified robotic system in order to carry out in-service inspection on above storage tanks (ASTs). Storage tanks are subject to corrosion over time, with potential environmental consequences, and it is expected that application of this robotic technology contributes to the prevention of corrosion more efficiently and with less risks considering the significant cost and health & safety risks associated with manual inspection of these tanks.
The current nautilUS robotic system is semi-autonomous. It has the capability of moving around a tank floor and can make measurements of the floor thinning using an ultrasound probe attached to it. The measurements, along with location data, are then recorded for post-processing after the robot is retrieved. However, this system still depends upon humans’/technicians' involvement, particularly when it comes to navigating the robot while it is inside the tank and analysis of floor thinning data once the data are collected and stored.
The project nautilUS + is currently at the proposal stage and it is going to focus on the ‘smart’ element. The initial evaluations show that multi-criteria decision-making (MCDM) and machine learning (ML) algorithms can be used together innovatively in order to contribute to the autonomy of the nautilUS robotic system with the potential of making it fully autonomous.
The current nautilUS robotic system is semi-autonomous. It has the capability of moving around a tank floor and can make measurements of the floor thinning using an ultrasound probe attached to it. The measurements, along with location data, are then recorded for post-processing after the robot is retrieved. However, this system still depends upon humans’/technicians' involvement, particularly when it comes to navigating the robot while it is inside the tank and analysis of floor thinning data once the data are collected and stored.
The project nautilUS + is currently at the proposal stage and it is going to focus on the ‘smart’ element. The initial evaluations show that multi-criteria decision-making (MCDM) and machine learning (ML) algorithms can be used together innovatively in order to contribute to the autonomy of the nautilUS robotic system with the potential of making it fully autonomous.
